Table 4_Data-driven intelligent productivity prediction model for horizontal fracture stimulation.xlsx by Qian Li (114642)

“…Finally, during fracturing design, the optimal productivity prediction model was matched to each interval based on its characteristics to predict post-fracturing productivity. …”

Table 1_Data-driven intelligent productivity prediction model for horizontal fracture stimulation.xlsx by Qian Li (114642)

“…Finally, during fracturing design, the optimal productivity prediction model was matched to each interval based on its characteristics to predict post-fracturing productivity. …”

Table 6_Data-driven intelligent productivity prediction model for horizontal fracture stimulation.xlsx by Qian Li (114642)

“…Finally, during fracturing design, the optimal productivity prediction model was matched to each interval based on its characteristics to predict post-fracturing productivity. …”

Table 3_Data-driven intelligent productivity prediction model for horizontal fracture stimulation.xlsx by Qian Li (114642)

“…Finally, during fracturing design, the optimal productivity prediction model was matched to each interval based on its characteristics to predict post-fracturing productivity. …”

Table 9_Data-driven intelligent productivity prediction model for horizontal fracture stimulation.xlsx by Qian Li (114642)

“…Finally, during fracturing design, the optimal productivity prediction model was matched to each interval based on its characteristics to predict post-fracturing productivity. …”

Table 7_Data-driven intelligent productivity prediction model for horizontal fracture stimulation.xlsx by Qian Li (114642)

“…Finally, during fracturing design, the optimal productivity prediction model was matched to each interval based on its characteristics to predict post-fracturing productivity. …”

Table 2_Data-driven intelligent productivity prediction model for horizontal fracture stimulation.xlsx by Qian Li (114642)

“…Finally, during fracturing design, the optimal productivity prediction model was matched to each interval based on its characteristics to predict post-fracturing productivity. …”

Personalized Dose Finding Using Outcome Weighted Learning by Guanhua Chen (1421857)

“…To estimate the optimal IDR using such data, we propose an outcome weighted learning method based on a nonconvex loss function, which can be solved efficiently using a difference of convex functions algorithm. …”

Fair Policy Targeting by Davide Viviano (14264992)

“…We adopt the nonmaleficence perspective of “first do no harm”: we select the fairest allocation <i>within</i> the Pareto frontier. We cast the optimization into a mixed-integer linear program formulation, which can be solved using off-the-shelf algorithms. …”

Image2_A Novel Deep Learning Method to Predict Lung Cancer Long-Term Survival With Biological Knowledge Incorporated Gene Expression Images and Clinical Data.JPEG by Shuo Wang (143908)

Image7_A Novel Deep Learning Method to Predict Lung Cancer Long-Term Survival With Biological Knowledge Incorporated Gene Expression Images and Clinical Data.JPEG by Shuo Wang (143908)

Table1_A Novel Deep Learning Method to Predict Lung Cancer Long-Term Survival With Biological Knowledge Incorporated Gene Expression Images and Clinical Data.XLSX by Shuo Wang (143908)

Image3_A Novel Deep Learning Method to Predict Lung Cancer Long-Term Survival With Biological Knowledge Incorporated Gene Expression Images and Clinical Data.JPEG by Shuo Wang (143908)

Image6_A Novel Deep Learning Method to Predict Lung Cancer Long-Term Survival With Biological Knowledge Incorporated Gene Expression Images and Clinical Data.JPEG by Shuo Wang (143908)

Image1_A Novel Deep Learning Method to Predict Lung Cancer Long-Term Survival With Biological Knowledge Incorporated Gene Expression Images and Clinical Data.JPEG by Shuo Wang (143908)

Image4_A Novel Deep Learning Method to Predict Lung Cancer Long-Term Survival With Biological Knowledge Incorporated Gene Expression Images and Clinical Data.JPEG by Shuo Wang (143908)

Image5_A Novel Deep Learning Method to Predict Lung Cancer Long-Term Survival With Biological Knowledge Incorporated Gene Expression Images and Clinical Data.JPEG by Shuo Wang (143908)

Metadata supporting the published article: A Medicare-based Comparative Mortality Analysis of Active Surveillance in Older Women with DCIS by Igor Akushevich (163135)

“…The final sample contained 22,576 female patients diagnosed with DCIS.…”

Data Sheet 1_A machine learning model for predicting the risk of diabetic nephropathy in individuals with type 2 diabetes mellitus.docx by Tingting Li (10553)

“…</p>Conclusions<p>The developed XGBoost model demonstrated optimal predictive accuracy for the occurrence of DKD in patients with T2DM. …”

<b>AI for imaging plant stress in invasive species </b>(dataset from the article https://doi.org/10.1093/aob/mcaf043) by Erola Fenollosa (20977421)

“…</i>, 2023</a>) (<a href="#sup1" target="_blank">Supplementary Data S2</a>). The final proposed betalain extraction procedure in the cape fig used 300 mg of frozen leaf samples ground with a mixer mill and homogenized with 0.5 mL of 50 % MeOH (aq.) and mixed for 20 min with a vortex. …”